Questions tagged [hyperparameter-tuning]
Hyperparameter tuning (also called hyperparameter optimization) refers to the process of finding the optimal set of hyperparameters for a given machine learning algorithm.
277 questions
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How to handle unstable best_iteration in LightGBM when using Optuna for hyperparameter optimization?
I'm using Optuna to optimize LightGBM hyperparameters, and I'm running into an issue with the variability of best_iteration across different random seeds. Current ...
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1 answer
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Should Hyperparameter Optimization Be Equalized by Trials or Compute Time?
Say I have two different models with different hyperparameters and I want to compare the performance of both models on some dataset. One model is much simpler than the other and, therefore, if I were ...
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How to interpret an unstable learning curve on a model tuned with Hyberband Tuning?
I have used Hyperband automatic tuning for an ANN model to predict price. After running the model with the automatic tuning, I am obtaining an R2 score of 1.00 that suggests overfitting, however, I am ...
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Can cross validation for tuning and LOO for evaluation on the exact same dataset cause bias?
I read two articles by the same guy where he uses the whole dataset for hyperparameter optimisation using with CV and then evaluates the model with the best hyperparameters using leave one out on the ...
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Which hyperparameters for a standard LLM provide the most benefit vs performance cost?
GPT3 has several hyper-parameters that define the network architecture. My question is: which of these hyper-parameters, when increased, provide the most performance benefit vs computational cost? ...
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Should I Use the Same Hyperparameters for Different Datasets in ML Models?
I am a student and am looking for your help. I have two datasets, including pre-treatment CT scan and post-treatment CT scan. I want to compare these datasets to determine which yields the best ...
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Error in plotting Gaussian Process for 3 models that use Bayesian Optimization
I'm writing a python script for Orange Data Mining to plot the gaussian processes in order to find the best hyperparameters for the 5-FoldCrossValidation Accuracy metric. The three models are SVC, ...
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What is the standard ML pipeline for training and testing? [closed]
I have a dataframe containing 1324 rows and 28 columns and I'm kinda lost on which approach to go for when training regression models. Currently I perform a data split and run GridSearchCV to pick the ...
